An Optimization of Energy-Efficiency in Machining Manufacturing Systems Based on a Framework of Multi-Mode RCPSP

Abstract

It has become important to consider energy-efficient optimization not only in a process design but also in the operations of manufacturing systems to promote sustainable and green manufacturing. This paper extends authors’ previous work to a more practical situation to demonstrate the applicability of the proposed framework of energy-efficient manufacturing operations based on a resource-constrained project scheduling problem (RCPSP). Both have varying resource requirements and multi processing modes, which can produce a suitable energy-load profiles for complete manufacturing systems. This study proposes a mathematical model for producing optimal energy-load profiles, and based on these profiles, each given operation is allocated to a machine tool with a specific processing mode. A processing mode refers to machining conditions for the corresponding operation, conditions that provide a predictive processing time and estimated electrical energy consumption. Through some cutting experiments on aluminum alloy performed on a three-axis machining center, we provide several possible processing modes for workpieces (operations), and we generate energy-load profiles by applying multi start local searches. We then discuss the applicability and capability of the energy-load profiles as an energy-aware production control.

Energy-Efficient Scheduling in Job Shop Manufacturing Systems: A Literature Review

“…The most common approach to the EEJSPs is to solve the JSP or the FJSP while optimizing an energy-related objective function. However, a few papers address energy efficiency concerns by imposing an upper limit on the total energy consumption (e.g., [21,22,34,63,64]) or on the peak power consumption (e.g., [65][66][67][68]). Of the 172 papers reviewed, 163 consider energy-related objective function(s).…”

Evaluation of Energy Efficiency and Productivity in Scheduling by Using Physical Simulator

“…This paper extends our previous work [6] on green manufacturing and investigates the relation between energy efficiency and productivity under a real circumstance based on the physically measured data including power consumption and uncertainties that can be observed in a specific physical system. Yonemoto et al [6] have developed a manufacturing simulator based on the what we call measurement and control platform [7], and demonstrated its embedded job sequence generator. A miniature factory model is utilized as a physical system to be connected to the developed simulator.…”